deploy

TimeSeriesFoundationModel.deploy(*, instance_type: str | None = None, endpoint_name: str | None = None, hyperparameters: dict[str, Any] | None = None, framework_version: str = '1.6', wait: bool = True, inference_mode: Literal['realtime', 'serverless'] = 'realtime', inference_config: dict[str, Any] | None = None, backend_overrides: dict[str, dict[str, Any]] | None = None, **kwargs: Unpack[DeployKwargs]) → TimeSeriesEndpoint[source]

Deploy the model to a real-time or serverless endpoint.

Parameters:

  • instance_type (str | None, default = None) – Instance type for the endpoint. Defaults to the model registry value. Must be None when inference_mode="serverless".

  • endpoint_name (str | None, default = None) – Name of the endpoint. If None, a unique name is generated.

  • hyperparameters (dict[str, Any] | None, default = None) – Model hyperparameters for inference. Overrides values passed to the constructor.

  • framework_version (str, optional) – AutoGluon version, e.g. “1.6”. Uses the official AutoGluon DLC image for this version.

  • wait (bool, default = True) – Whether to block until the endpoint is ready.

  • inference_mode (Literal["realtime", "serverless"], default = "realtime") – Endpoint type. "serverless" provisions a SageMaker Serverless Inference endpoint (no instance management, scales to zero).

  • inference_config (dict[str, Any] | None, default = None) – Serverless settings: memory_size_in_mb (default 4096), max_concurrency (default 5), and provisioned_concurrency.

Returns:

TimeSeriesEndpoint – Handle to the deployed endpoint.

Other Parameters:

  • backend_overrides (dict[str, dict[str, Any]] | None, default = None) – Raw SageMaker request fields for settings without a dedicated argument.

    • Keys: request names from the SageMaker API section below.

    • Values: request fields in PascalCase, as in the SageMaker API and boto3. Deep-merged over the request built by AutoGluon-Cloud; lists and other non-dict values replace the generated ones.

    • Example: {"ProductionVariant": {"ModelDataDownloadTimeoutInSeconds": 1200}}

  • initial_instance_count (int, default = 1) – Number of instances for the endpoint. Ignored when inference_mode="serverless".

  • volume_size (int | None, default = None) – Size in GB of the EBS volume to use for the endpoint. Ignored for GPU instances.

  • custom_image_uri (str | None, default = None) – Custom inference container image URI. If set, framework_version is ignored.

SageMaker API

The endpoint is billed until TimeSeriesEndpoint.delete_endpoint() deletes it.